Visual SLAM technology is one of the important technologies for mobile robots. Existing feature-based visual SLAM techniques suffer from tracking and loop closure performance degradation in complex environments. We propose the DFD-SLAM system to ensure outstanding accuracy and robustness across diverse environments. Initially, building on the ORB-SLAM3 …
As shown in Fig. 1, we develop an FPGA-based hardware accelerator to alleviate the computational load on the ARM processor in order to enhance the performance of dense stereo SLAM.This hardware accelerator is specifically designed to target the most time-consuming tasks, namely feature extraction, feature matching, and stereo matching.
Simultaneous Localization and Mapping (SLAM) plays a crucial role in enabling intelligent mobile robots and vehicles to estimate their state in unknown environments. …
The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of "localization" and "mapping". The visual semantic SLAM algorithm fused with semantic information enables robots to understand the surrounding environment better, thus …
Neural implicit representations have emerged as a promising solution for providing dense geometry in Simultaneous Localization and Mapping (SLAM). However, existing methods in this direction fall short in terms of global consistency and low latency. This paper presents NGEL-SLAM to tackle the above challenges. To ensure global consistency, our …
Image tracking and retrieval strategies are of vital importance in visual Simultaneous Localization and Mapping (SLAM) systems. For most state-of-the-art systems, hand-crafted features and bag-of-words (BoW) algorithms …
10w+,406,1.6k。SLAM?SLAM(simultaneous localization and mapping),CML (Concurrent Mapping and Localization),,。 …
With the application and development of probabilistic robots [], SLAM problems have gradually gained attention and development over the last decades, and related research …
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown significant performance, accuracy, and efficiency gains, especially when Neural Radiance Fields (NeRFs) are implemented. NeRF-based SLAM in mapping aims to implicitly understand irregular environmental information using large-scale parameters of deep learning networks in …
Equation 1 informs us that if want to get a quantity x that represents here a robot position based on measurement data d represents the odometry, we can do that by multiplying …
This paper describes a new near real-time visual SLAM system which adopts the continuous keyframe optimisation approach of the best current stereo systems, but accounts for the additional challenges presented by monocular input and presents a new pose-graph optimisation technique which allows for the efficient correction of rotation, translation and scale …
A contemporary trend in the field of simultaneous localization and mapping (SLAM) is the application of sensor fusion to improve performance. There are many sources of additional data, including but not limited to inertial measurement units (IMU), event cameras, and depth data. This paper introduces a visual monocular SLAM system that tightly combines …
In the past, manual inspection was often used for equipment inspection in indoor environments such as substation rooms and chemical plant rooms. This way often accompanies high labor intensity, low inspection efficiency, and low safety, which is difficult to meet the increasingly stringent requirements of indoor equipment operation and maintenance …
Appl. Sci. 2021, 11, 1828 4 of 15 In [16], an accelerator implemented in FPGA can expand the actual EKF‐SLAM (Extended Kalman Filter SLAM) system and observe and correct up to 45 landmarks
Simultaneous Localization And Mapping (SLAM) is a fundamental component used in many applications, such as robotic navigation and augmented reality. To achieve on …
Simultaneous localization and mapping (SLAM) is an active research topic in machine vision and robotics. It has various applications in many different fields such as mobile robots, augmented and ...
Visual simultaneous localization and mapping (vSLAM) serve as a core technology that can fuse image data collected by visual sensors on smart agents (e.g., robots, …
Appl. Sci. 2021, 11, 1828 4 of 15 For the LSD-SLAM (Large Scale Direct monocular SLAM) algorithm, Konstantinos Boikos et al. propose a hardware implementation based on an FPGA SoC (System-on-a-
Collaborative simultaneous localization and mapping (CSLAM) is essential for autonomous aerial swarms, laying the foundation for downstream algorithms, such as
Introduction to SLAM H and SLAMSYSTEM 417 4. RUN CONTROL Control statements are used to define experimental conditions such as the number of runs to make, run length, and when to …
This paper presents Navion, an energy-efficient accelerator for visual-inertial odometry (VIO) that enables autonomous navigation of miniaturized robots (e.g., nano drones), and virtual reality ...
In response to challenges such as variable lighting conditions, sparse texture information, and dynamic, unstructured environments, this paper introduces an innovative radarvision-inertial odometry system for Simultaneous Localization and Mapping (SLAM) in complex scenarios. …
Precise positioning in an indoor environment is a challenging task because it is difficult to receive a strong and reliable global positioning system (GPS) signal. For existing wireless indoor positioning methods, ultra-wideband (UWB) has become more popular because of its low energy consumption and high interference immunity. Nevertheless, factors such as …
